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to engage in pioneering research, collaborate with a large, dynamic and multidisciplinary team, and advance the field of quantum computing through innovative algorithms and technologies. This is an exciting
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techniques for integrating such solutions into modern SDV middleware. Responsibilities: Conduct research in runtime analysis and reconfiguration of in-vehicle TSN networks. Develop algorithms and prototypes
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integrate machine learning algorithms and Earth System Models to emulate carbon processes in the ocean connected to the biological activities. You will be enrolled in DTU’s Section for Oceans and Arctic and
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advanced AI algorithms to optimize and understand the optical properties of light-trapping surfaces. (more information can be found in the following News post ). You will work closely with colleagues both
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and nanostructuring, all guided by advanced AI algorithms to optimize and understand the optical properties of light-trapping surfaces. (more information can be found in the following News post ). You
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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to have experience with: Phase equilibrium calculation algorithms and their integration into CO2 capture simulation Thermodynamic modeling of phase equilibrium and thermophysical properties related to CO2
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will develop in the position; it is expected that you have previous experience on each of them: Develop and implement CFD models to simulate the behavior of PRO systems. Apply ML algorithms to optimise